• Proceedings of the Korea Water Resources Association Conference
• /
• 2006.05a
• /
• pp.149-153
• /
• 2006

Precipitation is the most important component and critical to the study of water and energy cycle. This study investigates the propagation of precipitation retrieval uncertainty in the simulation of hydrologic variables for varying spatial resolution on two different vegetation cover. We explore two remotely sensed rain retrievals (space-borne IR-only and radar rainfall) and three spatial grid resolutions. An offline Community Land Model (CLM) was forced with in situ meteorological data In turn, radar rainfall is replaced by the satellite rain estimates at coarser resolution $(0.25^{\circ},\;0.5^{\circ}\;and\;1^{\circ})$ to determine their probable impact on model predictions. Results show how uncertainty of precipitation measurement affects the spatial variability of model output in various modelling scales. The study provides some intuition on the uncertainty of hydrologic prediction via interaction between the land surface and near atmosphere fluxes in the modelling approach.

• KSCE Journal of Civil and Environmental Engineering Research
• /
• v.30 no.5D
• /
• pp.453-459
• /
• 2010

In the study of traffic safety, it is utmost important to obtain more reliable estimates of the expected crashes for a site (or a segment). The observed crashes have been mainly used as the estimate of the expected crashes in Korea, while the empirical Bayes (EB) estimates based on the Poisson-gamma mixture model have been used in the USA and several European countries. Although numerous studies have used the EB method for estimating the expected crashes and/or the effectiveness of the safety countermeasures, no past studies examine the difference in the estimation errors between the two estimates. Thus, this study compares the estimation errors of the two estimates using a Monte Carlo simulation study. By analyzing the crash dataset at 3,000,000 simulated sites, this study reveals that the estimation errors of the EB estimates are always less than those of the observed crashes. Hence, it is imperative to incorporate the EB method into the traffic safety research guideline in Korea. However, the results show that the differences in the estimation errors between the two estimates decrease as the uncertainty of the prior distribution increases. Consequently, it is recommended that the EB method be used with reliable hyper-parameter estimates after conducting a comprehensive examination on the estimated negative binomial model.

• Earthquakes and Structures
• /
• v.20 no.1
• /
• pp.97-107
• /
• 2021

A comprehensive study on seismic performance of wood frame building in hilly regions is presented. Specifically, seismic fragility assessment of a typical wood frame building at various locations of the northeast region of India are demonstrated. A three-dimensional simplified model of the wood frame building is developed with due consideration to nonlinear behaviour of shear walls under lateral loads. In doing so, a trilinear model having improved capability to capture the force-deformation behaviour of shear walls including the strength degradation at higher deformations is proposed. The improved capability of the proposed model to capture the force-deformation behaviour of shear wall is validated by comparing with the existing experimental results. The structural demand values are obtained from nonlinear time history analysis (NLTHA) of the three-dimensional wood frame model considering the effect of uncertainty due to record to record variation of ground motions and structural parameters as well. The ground motion bins necessary for NLTHA are prepared based on the identified hazard level from probabilistic seismic hazard analysis of the considered locations. The maximum likelihood estimates of the lognormal fragility parameters are obtained from the observed failure cases and the seismic fragilities corresponding to different locations are estimated accordingly. The results of the numerical study show that the wood frame constructions commonly found in the region are likely to suffer minor cracking or damage in the shear walls under the earthquake occurrence corresponding to the estimated seismic hazard level; however, poses negligible risk against complete collapse of such structures.

• Earthquakes and Structures
• /
• v.3 no.1
• /
• pp.17-35
• /
• 2012

Simplified equations for fundamental period of vibration of skeletal structures provided by most seismic design provisions suffer from the absence of any associated confidence levels and of any reference to their empirical basis. Therefore, such equations may typically give a sector of designers the false impression of yielding a fairly accurate value of the period of vibration. This paper, although not addressing simplified codes equations, introduces a set of mathematical equations utilizing the theory of error propagation and First-Order Second-Moment (FOSM) techniques to determine bounds on the relative error in theoretically calculated fundamental period of vibration of skeletal structures. In a complementary step, and for verification purposes, Monte Carlo simulation technique has been also applied. The latter, despite involving larger computational effort, is expected to provide more precise estimates than FOSM methods. Studies of parametric uncertainties applied to reinforced concrete frame bents - potentially idealized as SDOF systems - are conducted demonstrating the effect of randomness and uncertainty of various relevant properties, shaping both mass and stiffness, on the variance (i.e. relative error) in the estimated period of vibration. Correlation between mass and stiffness parameters - regarded as random variables - is also thoroughly discussed. According to achieved results, a relative error in the period of vibration in the order of 19% for new designs/constructions and of about 25% for existing structures for assessment purposes - and even climbing up to about 36% in some special applications and/or circumstances - is acknowledged when adopting estimates gathered from the literature for relative errors in the relevant random input variables.

• 한국지구물리탐사학회:학술대회논문집
• /
• 2007.12a
• /
• pp.63-72
• /
• 2007

Current estimates of the ice-mass balance over the Greenland and the Antarctica using retrievals of time-varying gravity from GRACE are presented. Two different GRACE gravity data, UTCSR RL01 and UTCSR RL04, are used for the estimates to examine the impact of the relative accuracy of background models in the GRACE data processing for inter-annual variations of GRACE gravity data. In addition, the ice-mass balance is appraised from the conventional GRACE data, which represents global gravity, and the filtered GRACE data, which isolates the terrestrial gravity effect from GRACE gravity data. The former estimate shows that there exists similar negative trends of ice-mass balance over the Greenland from UTCSR RL01 and UTCSR RL04 while the time series from the both GRACE data over the Antarctica differ significantly from each other, and no apparent trends are observed. The result for the Greenland from the latter calculation is similar to the former estimate. However, the latter calculation presents positive trends of ice-mass balance for the Antarctica from both GRACE data. These results imply that residual oceanic geophysical signals, particularly for ocean tides, significantly corrupt the ice-mass estimate over the Antarctica as leakage error. In addition, the spatial alias of GRACE is likely to affect the ice-mass balance because the spatial spectrum of ocean tides is not conserved via GRACE sampling, and thus ocean tides contaminate terrestrial gravity signal. To minimize the alias effect, I suggest to use the combined gravity models from GRACE, SLR and polar motion.

• Journal of Power Electronics
• /
• v.10 no.5
• /
• pp.498-504
• /
• 2010

The output power fluctuations of renewable energy power plants such as wind turbine generators and photovoltaic systems result in frequency deviations and terminal voltage fluctuations. Furthermore, these power fluctuations also affect the turbine shaftings of diesel generators and gas-turbine generators which are the main power generation systems on isolated islands. Therefore, it is important to achieve torsional torque suppression. Since the measurement of torsional torque is technically difficult, and there is an uncertainty in the mechanical constants of the shaft torsional system. This paper presents an estimation system that estimates torsional torque by using a developed $H_{\infty}$ observer. In addition to the above functions, the proposed shaft torque observer incorporates a parameter identification system that aims to improve the estimation accuracy. The simulation results validate the effectiveness of the proposed $H_{\infty}$ observer and the parameter identification.

• Physical Therapy Korea
• /
• v.23 no.2
• /
• pp.93-99
• /
• 2016

Background: Parametric statistical procedures are typically conducted under the condition in which a sample distribution is statistically identical with its population. In reality, investigators use inferential statistics to estimate parameters based on the sample drawn because population distributions are unknown. The uncertainty of limited data from the sample such as lack of sample size may be a challenge in most rehabilitation studies. Objects: The purpose of this study is to review the bootstrapping method to overcome shortcomings of limited sample size in rehabilitation studies. Methods: Articles were reviewed. Results: Bootstrapping method is a statistical procedure that permits the iterative re-sampling with replacement from a sample when the population distribution is unknown. This statistical procedure is to enhance the representativeness of the population being studied and to determine estimates of the parameters when sample size are too limited to generalize the study outcome to target population. The bootstrapping method would overcome limitations such as type II error resulting from small sample sizes. An application on a typical data of a study represented how to deal with challenges of estimating a parameter from small sample size and enhance the uncertainty with optimal confidence intervals and levels. Conclusion: Bootstrapping method may be an effective statistical procedure reducing the standard error of population parameters under the condition requiring both acceptable confidence intervals and confidence level (i.e., p=.05).

• Journal of Preventive Medicine and Public Health
• /
• v.36 no.3
• /
• pp.230-238
• /
• 2003

Objectives : To estimate the value of statistical life (VSL) and health damage cost on theoretical mortality estimates due to environmental pollution. Methods : We assessed the health risk on three environmental problems and eight sub-problems. Willingness to pay (WTP) was elucidated from a questionnaire survey with dichotomous contingent valuation method and VSL (which is the division of WTP by the change of risk reduction) calculated from WTP. Damage costs were estimated by multiplying VSL by the theoretical mortality estimates. Results : VSLs from death caused by air pollution, indoor air pollution and drinking water contamination were about 0.3, 0.5 and 0.3 billion won, respectively. Damage costs of particulate matters ($PM_{10}$) and radon were higher in the sub-problems and were above 100 billion won. Because damage cost depends on theoretical mortality estimate and WTP, its uncertainty is reduced in the estimating process. Conclusion : Health damage cost or risk benefit should be considered as one scientific criterion for decision making in environmental policy.

• Journal of Korean Society of Transportation
• /
• v.30 no.1
• /
• pp.135-147
• /
• 2012

The benefit of traffic information on variable message sign can be divided into two. At the public level, the benefit of ATIS is the travel time saving, which is not only induced from ATIS, but also mixed with that of ATMS. In the economic appraisal of ITS, the benefit of ATIS has so far been regarded as the derived benefit from ATMS. At the user level, the benefit of ATIS is reduced driver uncertainty through the forward traffic status information. User can benefit from the information on VMS and therefore may have the willingness to pay for it. Recently attempt to qualify the value of information on VMS was increased, but there was a danger of distorting or over-estimates of the ATIS benefit because the related studies didn't consider the time-dependent attributes of traffic information and provided the single value. Estimates of the time-varying value should be needed for a rigorous economic appraisal of ATIS. In this study, we varied the value of information on VMS according to peak and non peak trip and verified the hypothesis that time-varying of value was statistically significant.

• Journal of the Korean earth science society
• /
• v.31 no.4
• /
• pp.301-312
• /
• 2010

Geochemical data have been regarded as one of the important environmental variables in the environmental management. Since they are often sampled at sparse locations, it is important not only to predict attribute values at unsampled locations, but also to assess the uncertainty attached to the prediction for further analysis. The main objective of this paper is to exemplify how indicator geostatistics can be effectively applied to geochemical data processing for providing decision-supporting information as well as spatial distribution of the geochemical data. A whole geostatistical analysis framework, which includes probabilistic uncertainty modeling, classification and risk analysis, was illustrated through a case study of cadmium mapping. A conditional cumulative distribution function (ccdf) was first modeled by indicator kriging, and then e-type estimates and conditional variance were computed for spatial distribution of cadmium and quantitative uncertainty measures, respectively. Two different classification criteria such as a probability thresholding and an attribute thresholding were applied to delineate contaminated and safe areas. Finally, additional sampling locations were extracted from the coefficient of variation that accounts for both the conditional variance and the difference between attribute values and thresholding values. It is suggested that the indicator geostatistical framework illustrated in this study be a useful tool for analyzing any environmental variables including geochemical data for decision-making in the presence of uncertainty.